Senior Staff Machine Learning Platform Engineer

This is a fully remote position, open to applicants in Arizona, +30 more states.

📋 Description

• Take ownership of the technical vision and advancement of Faire’s machine learning platform.

• Define and steer long-term architecture encompassing training, inference, feature management, and governance.

• Set company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability.

• Lead the adoption and sophisticated use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns.

• Design scalable ML workflows utilizing Spark, Delta Lake, and MLflow.

• Enhance platform performance, reliability, and cost-efficiency.

• Assess and incorporate emerging features from Databricks.

• Stay updated with the latest advancements in machine learning and AI.

• Serve as a senior ML technical advisor to Faire’s data science and production engineering teams.

• Represent Faire at machine learning conferences and meetups.

• Mentor ML engineers and elevate the overall machine learning standards at Faire.

⛳️ Requirements

• 10-12 years of experience in building and enhancing large-scale ML or data platforms.

• A degree in Computer Science, Engineering, Statistics, or a related technical field (graduate level preferred).

• In-depth expertise in Databricks lakehouse architecture, including Unity Catalog governance, workflow orchestration, and cost optimization.

• Capability to design systems that support multiple data science teams and production workloads.

• Strong background in distributed systems, ML infrastructure, and cloud architecture.

• Proven technical leadership across teams and organizations.

• Proficiency in Python, SQL, Kotlin, PyTorch, PySpark, MLflow, Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL, AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform, Claude Sonnet 4.5, and ChatGPT 5.2.

• Experience integrating LLM workflows into enterprise platforms is a plus.

• Contributions to open-source ML infrastructure projects or research publications are a strong plus.

🏝️ Benefits

• Equity

• Comprehensive benefits

• Latest enterprise AI tools

• Competitive pay

• Equal access to opportunities, growth, and success

• Reasonable accommodation throughout the recruitment process

• Hybrid employees may work remotely up to 4 weeks per year